将( dplyr tbl-对象的)列转换为tbl头。

Question

我有一个data.frame如下所示：

     types       long_name
     (chr)           (chr)
1  neighborhood Upper East Side
2  sublocality  Manhattan
3  postal_code  10021

我想对它作如下修改：

     neighborhood    sublocality   postal_code
     (chr)           (chr)         (chr)
1  Upper East Side   Manhattan     10021

必须有一种快速而简单的方法来做到这一点。

编辑注意:这不是作为一个R数据note显示的，而是显示为一个dply对象：

dput(as.tbl(dfrm))
structure(list(types = c("neighborhood", "sublocality", "postal_code"
), long_name = c("Upper East Side", "Manhattan", "10021")), .Names = c("types", 
"long_name"), class = c("tbl_df", "tbl", "data.frame"), row.names = c(NA, 
-3L))

Answer 1

坚持使用Hadleyverse，我们可以使用tidyr::spread从长到宽：

library(tidyr)

df %>% spread(types, long_name)
# Source: local data frame [1 x 3]
# 
#      neighborhood postal_code sublocality
#             (chr)       (chr)       (chr)
# 1 Upper East Side       10021   Manhattan

Answer 2

将types设置为long_name向量上的名称，然后在其上运行as.data.frame.list()。假设df是您的数据框架..。

as.data.frame.list(
    with(df, setNames(long_name, types)), 
    stringsAsFactors = FALSE
)
#      neighborhood sublocality postal_code
# 1 Upper East Side   Manhattan       10021

或者，同样的事情有点不同的方式.

as.data.frame(
    with(df, setNames(as.list(long_name), types)),
    stringsAsFactors = FALSE
)

如果需要数字邮政编码，请在该列上运行as.numeric()。此外，由于您使用的是dplyr，所以您可以通过在tbl_df()中包装这个结果来获得您的确切愿望结果。或者你可以在dplyr中做所有的事情，比如

df %>%
    do(
        as.data.frame.list(
            setNames(.$long_name, .$types), 
            stringsAsFactors = FALSE
        )
    ) %>%
    tbl_df
# Source: local data frame [1 x 3]
#
#      neighborhood sublocality postal_code
#             (chr)       (chr)       (chr)
# 1 Upper East Side   Manhattan       10021

数据：

df <- structure(list(types = c("neighborhood", "sublocality", "postal_code"
), long_name = c("Upper East Side", "Manhattan", "10021")), .Names = c("types", 
"long_name"), row.names = c(NA, -3L), class = c("tbl_df", "tbl", 
"data.frame"))

Answer 3

我们可以使用transpose

library(data.table)
setNames(transpose(df[-1]), df$types)
#     neighborhood sublocality postal_code
#1 Upper East Side   Manhattan       10021